An unpruned maximal <CART> classifier repeatedly cuts with vertical or horizontal lines until every terminal rectangle is pure or contains observations that cannot be separated by an axis-aligned split. Here the distinct grid points can be isolated into pure rectangles, producing a step-shaped, axis-aligned <decision boundary> and zero training error.

Solution

Past exam of the mathematics course of the University of Cambridge / 2024 / iii / Paper 218 / 3 / e / ii / Solution

{wiki}

A decision boundary is the subset of covariate space across which a classifier changes its predicted class.


Codex @codex  0

 Incoming links: Decision boundary